---
title: "Deploy Pipe, tools, and memory on Langbase"
description: "Learn how to run a summarizer pipe in Node.js using BaseAI."
tags:
    - baseai
    - langbase
    - learn
    - pipe
    - tool
    - memory
    - deploy
section: "deploy"
published: 2024-09-24
modified: 2024-09-24
---

# Deploy Pipe, tools, and memory on Langbase

### Learn how to deploy pipes, tools, and memory on Langbase

<Note sub="/learn">
This guide is part of the /learn BaseAI course. For context, [start from the beginning](/learn) to follow along.
</Note>

---

In this learn guide, you will deploy the summarizer pipe, tools, and memory on Langbase.

---

## Step #1: Authenticate with Langbase (optional)

We will deploy the AI pipe, tool and memory on Langbase to use it as a highly scalable API. If you have already authenticated with Langbase, you may skip this step. However, if this is your first time, please authenticate using the following command:

```bash
npx baseai@latest auth
```

## Step #2: Deploy on Langbase

To deploy the pipe, tool, and memory, run the following command:

```bash
npx baseai@latest deploy
```

This will deploy the pipe to Langbase and return the URL of the deployed pipe. The pipe deployment happens in three different ways which you can read [here](/docs/deployment/deploy).

---

Congratulations! You have successfully:

-  **Created** a summarization agent AI pipe.
-  **Ran** the AI pipe with configuration and meta settings.
-  **Created** a weather tool that returns the current weather for a given location.
-  **Integrated** the tool in the agent pipe.
-  **Ran** the AI pipe with the integrated tool.
-  **Created** a memory and add documents to it.
-  **Embeded** the memory to generate embeddings for the documents.
-  **Integrated** the memory with the agent pipe.
-  **Ran** the AI pipe with the integrated memory.
-  **Deployed** your AI features to Langbase API (global, highly available, and scalable) for production.

---
